Hub members Have many expertise, covering most of the fields in bioinformatics and biostatistics. You'll find below a non-exhaustive list of these expertise
Searched keyword : Metabolomics
Related people (2)
After a PhD in informatics on graph analysis (metabolic networks and sRNA-mRNA interaction graphs) at the LaBRI (Université de Bordeaux), I joined the DSIMB team (INTS) for a post-doc on structural modeling. Then, I performed a second post-doc at Metagenopolis – INRA Jouy-en-Josas, where I was initiated to the analysis of metagenomic data. I was recruited at the HUB in 2015, and since I pursue the development of methods dedicated to the treatment of metagenomic data by combining either the treatment of sequencing data, the statistics, the protein structural modeling and the graph analysis.
AlgorithmicsClusteringGenome assemblyGenomicsMetabolomicsModelingNon coding RNASequence analysisStructural bioinformaticsTargeted metagenomicsDatabaseGenome analysisBiostatisticsProgram developmentScientific computingDatabases and ontologiesExploratory data analysisData and text miningIllumina HiSeqComparative metagenomicsRead mappingIllumina MiSeqSequence homology analysisGene predictionMultidimensional data analysisSequencingShotgun metagenomics
- Targeted search of specific commensals in 16S databases(Pamela SCHNUPF - Molecular Microbial Pathogenesis) - In Progress
- Microbiota dysbiosis in human colon cancer(Iradj SOBHANI - Other) - Pending
- Environmental and human surveillance of polioviruses, VDPVs, and other enteroviruses in Madagascar and the impact during the switch from tOPV to bOPV(Patsy POLSTON - Biology of Enteric Viruses) - In Progress
A computer scientist by training, I am applying this knowledge to solve biological problems and am particularly interested in modelling of biological systems, knowledge inference, ontologies and data visualisation.
AlgorithmicsData VisualizationMetabolomicsModelingPathway AnalysisPhylogeneticsSystems BiologyTool DevelopmentDatabaseProgram developmentScientific computingDatabases and ontologiesApplication of mathematics in sciencesSofware development and engineeringData and text miningEvolutionData integrationGraph theory and analysisWorkflow and pipeline developmentDiscrete and numerical optimization
VirusHuman Immunodeficiency virus (HIV)
- Modeling mitochondrial metabolism dormant Cryptococcus neoformans(Benjamin HOMMEL - Molecular Mycology) - In Progress
- Measles virus protein C interplay with cellular apoptotic pathways; applications for cancer treatment(Alice MEIGNIÉ - Viral Genomics and Vaccination) - In Progress
- Diffusion des mutations de résistance du VIH : modèles et méthodes d’estimation(Olivier GASCUEL - Evolutionary Bioinformatics) - In Progress
Related projects (3)
The aim of the project is to create a viewer that will help visualisation and correlation between genomic, transcriptomic, proteomic and metabolomic data generated by the comparison of amastigote and promastigote stages of the Leishmania donovani parasite.
Innate lymphoid cells (ILCs) are the most recently identified components of the innate immune system. ILCs colonize different tissue sites and react promptly to microenvironmental perturbations. Due to their high plasticity, ILCs can shape their functional output in response to local cues. As such, ILCs play roles under homeostatic conditions and in the context of infection, chronic inflammation, metabolic diseases and cancer. Diverse ILC subsets (NK cells, ILC2) have been shown to regulate the metabolic homeostasis. Metabolic states affect cellular functions and have been shown to play an important role in the regulation of adaptive immunity. In contrast, almost nothing is known about innate lymphocytes metabolism and the importance of energy regulation for ILC function. This project will study metabolic profiles in human ILC subsets under diverse environmental conditions. Enhancing or interfering with ILC activity could ultimately represent a novel useful therapy for chronic inflammatory diseases.
We have shown that chronic stress impact gut microbiota and leads also to metabolomic abnormalitites . We want here to decipher whether particular gut bacterial species could be directly link to the metabolism differences we observed.